• 한국시뮬레이션학회논문지
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• 제14권3호
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• pp.91-100
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

• International Journal of Precision Engineering and Manufacturing
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• 제6권3호
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• pp.37-44
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• 2005

Gait control capacity for most trans-femoral prostheses is significantly different from that of a normal person, and training is required for a long period of time in order for a patient to walk properly. People become easily tired when wearing a prosthesis or orthosis for a long period typically because the gait angle cannot be smoothly adjusted during wearing. Therefore, to improve the gait control problems of a trans-femoral prosthesis, the proper gait angle is estimated through surface EMG(electromyogram) signals on a normal leg, then the gait posture which the trans-femoral prosthesis should take is calculated in the neural network, which learns the gait kinetics on the basis of the normal leg's gait angle. Based on this predicted angle, a postural control method is proposed and tested adaptively following the patient's gait habit based on the predicted angle. In this study, the gait angle prediction showed accuracy of over $97\%$, and the posture control capacity of over $90\%$.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.445-450
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• 1998

In this paper, a robust nonlinear prediction-type controller (RNPC) is developed for the continuous time nonlinear system whose control objective is composed of system output and its desired value. The basic control law of RNPC is derived such that the future response of the system is first predicted by appropriate functional expansions and the control law minimizing the difference between the predicted and desired responses is then calculated. RNPC which involves two controls, i.e., the auxiliary and robust controls into the basic control, shows the stable closed loop dynamics of nonlinear system of any relative degree and provides the robustness to the nonlinear system with parameter/modeling uncertainty. Simulation tests for the position control of a two-link rigid body manipulator confirm the performance improvement and the robustness of RNPC.

• 한국음향학회지
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• 제21권8호
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• pp.703-707
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• 2002

새로운 콘트롤 밸브 소음 예측 방법을 제안하고 밸브 및 배관으로 이루어진 시스템에 적용하여 그 가능성을 할인하였다. 기존의 소음 예측 방법은 무향실을 이용하는 기존의 예측방법보다 일반 산업체에서 시험 시설을 설치하기가 용이한 장점이 있다. 측정된 음향파워를 이용하여 소음예측식을 결정하고 상대유량계수 0.11인 경우 소음예측식에 따라 유량 및 차압의 변화에 따른 음향파워레벨을 평가하였고 그 결과가 측정값과 잘 일치함을 확인하였다. 제안된 밸브소음 예측기법은 콘트롤밸브의 소음특성을 나타내는 지표로서 사용할 수 있다.

• 상하수도학회지
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• 제22권2호
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• pp.213-218
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• 2008

Prediction models for post-chlorination require complicated information of reaction time, chlorine dosage considering flow rate as well as environmental conditions such as turbidity, temperature and pH. In order to operate post-chlorination process effectively, the correlations between inlet and outlet of clear well were investigated to develop prediction models of chlorine dosages in post-chlorination process. Correlations of environmental conditions including turbidity and chlorine dosage were investigated to predict residual chlorine at the outlet of clear well. A linear regression model and autoregressive model were developed to apply for the post-chlorination which take place time delay due to detention in clear well tank. The results from autoregressive model show the correlationship of 0.915~0.995. Consequently, the autoregressive model developed in this study would be applicable for real time control for post chlorination process. As a result, the autoregressive model for post chlorination which take place time delay and have multi parameters to control system would contribute to water treatment automation system by applying the process control algorithm.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.46-51
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• 2011

High-rise buildings are widely being constructed in the Middle-East, South-East, and East Asia. These buildings are usually willing to stand for the landmark of the region and, therefore, exhibit some extraordinary features such as super-tall height, elevation set-backs, overhangs, or free-form exterior surface, all of which makes the construction difficult, complex, and even unsafe at some construction stages. In addition to the elaborately planned construction sequence, prediction and monitoring of building's movement during construction and after completion are required for precise and safe construction. This is often called the Building Movement Control during construction. This study describes Building Movement Control of the KLCC Tower, a 58-story office building currently being built right next to the famous PETRONAS Twin Towers. The main items of the Building Movement Control for the KLCC Tower are axial shortening and verticality. Preliminary prediction of these items are already carried out by the structural design team but more accurate prediction based on construction stage analysis and combined with time-dependent material testing, field monitoring, and site survey is done by the main contractor. As of September 2010, the Tower is under construction at level 30, where the plan abruptly changes from rectangle to triangle. Findings and troubleshooting until the current construction stage are explained in detail and implementations are suggested for future applications.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.723-727
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• 2003

In this paper, two methods are discussed for good rolling force prediction in a plate mill. One is about the development of a long and a short learning scheme using a Neural Network for normal rolling and the other is about a mathematical model improvement by considering microstructural changes for controlled rolling. The research results are implemented in a on-line system of Pohang Works in POSCO and the field tests have showed that the prediction accuracies of rolling force are highly improved.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.219-224
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• 1988

A decentralised computational procedure is proposed for the optimal feedback gain matrix of large-scale discrete-time systems with time-delays. The constant feedback gain matrix is computed from the optimal state and input trajectries obtained hierarchically by the interaction prediction method. All the calculation in this approach are done off-line. The resulting gains are optimal for all the initial conditions. The interaction prediction method is applied to time-delay large-scale systems with general structures by extending the dimensions of coupling matices. A numerical exampie illustrates the algorithm.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권1호
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• pp.1-10
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• 2005

This paper proposes a new and simple input prediction method for robust servo system. A robust tracking control system for optical disk drives was proposed recently based on both Coprime Factorization (CF) and Zero Phase Error Tracking (ZPET) control. The CF control system can be designed simply and systematically. Moreover, this system has not only stability but also robustness to parameter uncertainties and disturbance rejection capability. Since optical disk tracking servo system can detect only tracking error, it was proposed that the reference input signal for ZPET could be estimated from tracking errors. In this paper, we propose a new control structure for the ZPET controller. It requires less memory than the previously proposed method for the reference signal generation. Numerical simulation results show that the proposed method is effective.